Association between psychosocial determinants of adverse childhood experiences and severe early childhood caries among First Nations children
Bibliographic record
Abstract
AIM: To determine whether psychosocial determinants of adverse childhood experiences (ACE), from pregnancy to 2 years old, are associated with severe early childhood caries (S-ECC) in Indigenous children. DESIGN: Secondary data analyses from an ECC prevention trial among 344 First Nations mother-child dyads living on- and off-reserve in Ontario and Manitoba, Canada. Stratified (on-/off-reserve) logistic regression, controlling for mother's age and income source, assessed three categories of psychosocial ACE determinants: alcohol/drug misuse, household financial hardship (overcrowding and food insecurity) and emotional/social well-being (Perceived Stress Scale (PSS-14), sense of personal control (SOC), social support, subjective social status). RESULTS: Household overcrowding [adjusted odds ratio (AOR) = 1.89 (95% CI: 1.06-3.38)], food insecurity [AOR = 2.86 (1.53-5.34)] and mothers' high perceived stress [AOR = 2.48 (1.40-4.37)] were associated with S-ECC (dmft > 9) for those on-reserve. Maternal SOC had a protective effect for off-reserve children [AOR = 0.17 (0.03-0.95)]. CONCLUSIONS: Increased efforts to reduce psychosocial ACE determinants are paramount to decreasing Indigenous children's vulnerability to S-ECC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".